It is well known to employ transform coding of digital images for bandwidth compression prior to transmission over a limited bandwidth communication channel. In a typical prior art digital image compression and transmission system employing transform coding, the digital image is formatted into blocks (e.g. 16.times.16 pixels) and a spatial frequency transformation such as a discrete cosine transform, DCT, is applied to each block to generate 16.times.16 blocks of transform coefficients. Theoretical and simulation studies have shown that the DCT is nearly optimum for reducing redundancy of first-order Markov image models. It has been shown to be very close to the Karhunen-Loeve Transform, which is optimal in reducing redundancy, but which does not yield to a straight forward computation like the DCT. Each block of transform coefficients is ordered into a one-dimensional vector such that the average energy of each coefficient generally decreases along the vector. The nonzero transform coefficients are quantized and coded using a minimum redundancy coding scheme such as Huffman coding; run-length coding is used to encode runs of coefficients having zero magnitude. The coded transform coefficients are transmitted over the limited bandwidth channel. See U.S. Pat. No. 4,302,775 issued Nov. 24, 1981 to Widergren et al for an example of such a compression scheme in a a video image compression system.
At the receiver, the image signal is decoded using operations that are the inverse of those employed to encode the digital image. This technique is capable of producing advantageously high image compression ratios, thereby enabling low bit rate transmission of digital images over limited bandwidth communication channels.
It has further been suggested that incorporation of a model of the human visual system in an image compression technique should further improve its performance (See "Visual Model Weighted Cosine Transform for Image Compression and Quality Assessment" by Norman B. Nill IEEE Transactions on Communications, Vol. COM-33, No. 6, June 1985)
It is the object of the present invention to provide an improved image compression technique incorporating a model of the human visual system.